A Novel Image Classification Algorithm Using Overcomplete Wavelet Transforms
Abstract— A Novel Image Classification Algorithm Using Overcomplete Wavelet Transforms. A novel frequency-based classiﬁcation framework and new wavelet algorithm (Wave-CLASS) is proposed using an over complete decomposition procedure. This approach omits the down sampling procedure and produces four-texture information with the same dimension of the original image or window at inﬁnite scale. Three image subsets of Quick Bird data < Final Year Projects 2016 > i.e., park, commercial, and rural over a central region in the city of Phoenix were used to examine the effectiveness of the new wavelet over complete algorithm in comparison with a widely used classical approach (i.e., maximum likelihood). While the maximum-likelihood classiﬁer produced as a 78.29% overall accuracies for all three image subsets.